Vibe Compiler: A Research-Logic Synthesis Tool That Runs without Prompt Engineering -Toward Enhancing Metacognition for Sustaining Agency in the Age of Generative AI-

2026-08-05

AI Summary

This study addresses the risk that generative AI, when used to support research, may lead users to uncritically accept its outputs, thereby undermining human cognitive agency. To counter this, the authors propose a Synthesis-Analysis Reciprocity Model and implement it in the Vibe Compiler system, which translates researchers’ vague intuitions (“Vibes”) into rigorous logical structures via a 16-dimensional academic ontology. When logical gaps are detected, the system prompts users with reflective questions to autonomously complete the reasoning rather than relying on AI-generated content. The work innovatively categorizes four origins of logical discontinuities and introduces a mechanism whereby the AI actively interrogates its own outputs to stimulate human metacognition. Prototype evaluation demonstrates that effective AI-assisted reasoning depends more on structured knowledge inputs than on sophisticated prompt engineering, significantly reinforcing researchers’ critical agency in human-AI collaboration.

Abstract

Generative AI used as a capable servant has greatly accelerated intellectual work, but it also risks eroding human epistemic agency by encouraging uncritical acceptance of AI-generated reasoning. This creates a need for mechanisms that preserve human agency by augmenting metacognition during AI-assisted intellectual work. To address this, we propose the Synthesis-Analysis Reciprocity Model, which views intellectual construction as a reciprocal interaction between Synthesis, which combines components into an artifact, and Analysis, which critically evaluates them against objective indicators and constrains subsequent synthesis. Grounded in this model, we present the Vibe Compiler, a research-logic compiler that helps researchers transform vague ideas (Vibes) into coherent research logic. The system compiles these ideas using a research paper ontology of sixteen academic parameters. Compilation failures indicate missing logical components; rather than filling them autonomously, the system prompts researchers with reflective questions that encourage them to develop the missing reasoning. The framework characterizes structural gaps along two dimensions: cognitive function (Synthesis vs. Analysis) and executing agent (human vs. AI), yielding four origin types that identify where breakdowns arise. Our design emphasizes AI probing its own synthesized output to stimulate human metacognition, encouraging researchers to remain managers who critically direct and validate AI-generated reasoning rather than passive recipients. Experience with a prototype built on NotebookLM and Gemini suggests that effective AI-assisted reasoning depends less on sophisticated prompting than on the knowledge structure provided to the AI. This paper was developed using the proposed Vibe Compiler.

Problem

• epistemic agency
• metacognition
• generative AI
• intellectual work
• human-AI collaboration

Innovation

• metacognition
• research-logic synthesis
• Synthesis-Analysis Reciprocity Model
• Vibe Compiler
• epistemic agency